Professional Summary

• SAS Certified Base programmer
• Experienced in programming and data management using SAS 9
• Experienced in Data Analysis, Data Modeling, Data Migration, and Reporting
• Demonstrated high level of proficiency in SAS programming with expertise in
• Importing and exporting raw data files
• Manipulating and transforming data
• Combining SAS data sets
• Developing detail and summary reports using SAS procedures
• Identifying and correcting data, syntax and programming logic errors.
• Using advanced DATA step programming statements and efficiency techniques to solve complex problems
• Writing and interpreting SAS SQL code
• Creating and using the SAS MACRO facility.
• Good understanding of programming standards and software development best practices
• Experienced in working with requirement analysts, developers, and testers for complex projects during the full Software Development Life Cycle (SDLC)
• Excellent team player with strong analytical, problem solving, interpersonal skills and quick learning abilities

Relevant Skills

SAS 9 and Microsoft Office Suites of products

Visual Basic, VBA

MS Windows, Linux/Unix

MS SQL Server, MS Access

Education

Certification and Professional Courses

Professional Experience

Project Name: Credit Risk Modeling

Role: Credit Risk Analyst

Environment : Windows XP, VBA in Microsoft Excel

August 2011 - December 2011

This project focused on validating the accuracy of the subscribed data service used by Key Bank that provides it with the Probability of Default for its current and prospective clients. Trading desk at Key Bank also used this service, which helps it to make future trades in the market. Critical part of this project was to collect data related to the client's debt structure and developing credit models. The project team consisted of Head of Credit Portfolio Management at Key Bank and three other members from the trading desk.

In this role, my responsibilities were as follows:

• Prepared project proposal document listing objectives and deadlines
• Acquired, designed and developed panel data related to client's income statement, balance sheets and historical equity performance.
• Developed fundamental credit risk models, using the panel data, against which to validate the subscribed service used by Key Bank
• Performed predictive analysis to estimate the probability of default for 10 public companies. Analyzed key statistic measures such as correlation, performed chi-square test
• Applied VBA in Excel skill set to program these complex credit models
• Lead the PowerPoint presentation with team of (4 people), explaining our result and model limitations to group of Key Bank employees

Project Name: Mutual Funds: Analyzing Managers, Performance and Style

Role: SAS Developer

Environment : Windows XP, SAS Base 9.2, SAS Macro

May 2011 - June 2011

The purpose of the project was to analyze returns of over 6,000 mutual funds by calculating performance ratios and assigning the mutual funds a particular style based on the regression performed with certain variables. The style to which each mutual fund should belong was small cap value fund, large cap value fund, small cap growth fund and large cap growth fund.

In this role, my responsibilities were as follows:

• Perform Data Validation and Data Cleaning as the project required data to be used only until December 2007 to avoid the bias of financial crisis.
• Extensive use of Proc SQL to create tables, join tables and perform queries
• Data profiling to calculate the sample statistics of returns for each type of fund including mean, median, standard deviation and standard error
• Develop macro to determine fund's performance and style
• Performed OLS regression in SAS and analyzed the coefficients
• Generate t-statistics and create a table breaking down over 6,000 mutual funds based on their returns and style.

Project Name: Empirical Finance Project

Role: SAS Programmer

Environment : Windows XP, SAS Base 9.2, SAS SQL Facility

January 2011 - April 2011

The objective of the project was to identify and analyze the rationale behind stock splits. The primary purpose of the report was to understand what drives the stock split decision. The challenges faced were the project used a dummy variable to run the regression. As such, OLS regression was not useful and instead used logistic regression. The project extensively used SAS to analyze statistically the stock split data over 5-year timeframe.

In this role, my responsibilities were as follows:

• Collect, design and analyze data on stock splits by establishing connection to SAS from external databases such as Wharton Research Data Services
• Use SQL in SAS to perform queries and maintain data quality
• Use ODS output options to create PDF and RTF files and ODS graphics to generate graphs
• Perform logistic regression on the variables in SAS
• Perform data profiling and analyze the model sample statistic and generated reports of the results in SAS

Project Name: Event Study Research Project

Role: SAS Programmer

Environment : Windows XP, Base SAS 9.2, SAS Macro, SAS SQL Facility

August 2010 - December 2010

This project required creating a macro in SAS to generalize the computation of abnormal returns and cumulative abnormal returns around specific events in stock market. The macro takes number of parameters and produces a printed output and graph of returns around the event date. Events included inclusion in S & P 500, Mergers & Acquisition and Initial Public Offering. Critical part of the project was to access the data from various sources and performing data validation and data cleaning.

In this role, my responsibilities were as follows:

• Programming in SAS to calculate abnormal returns around these special events
• Extensively using PROC IMPORT and IMPORT wizard to access and develop data stored in Microsoft Excel.
• Establishing remote connection through the use of SAS Connect
• Performing data profiling to statistically analyze data and calculate measures such as t-statistic.
• Performing Data Cleaning and Data Validation using statistical procedures like Proc Freq, Proc Means and Proc Univariate
• Helping to resolve data quality issues
• Performing functions like joining tables, writing queries through PROC SQL in SAS.
• Debugging the macro thorough the use of SYMBOLGEN and MLOGIC system options